There are various geographic linear features in remote sensing images, such as roads, railways, rivers, coastlines and the like. Identification of linear features from remote sensing images is a topic attracting much interest from researchers. Due to the significance of roads and the need of updating Geographic Information Systems (GIS), scientists and researchers used to pay much attention to road extraction. During the past several decades, many researchers proposed different methods to extract road information from high resolution remote sensing images such as aerial imagery, synthetic aperture radar (SAR) images and satellite images.
Another important object in remote sensing images is power transmission lines. Conventionally, research focused mainly on extracting information of power transmission lines from LiDAR images, helicopter aerial images, and unmanned aerial vehicle (UAV) optical images. Such information is used to inspect power transmission lines to guarantee the safety of power transmission and distribution lines as well as that of the related equipment. Up until now, there is little research on extracting power lines from remote sensing satellite images.
Rapid development of space technology over the past decade makes it possible to take satellite images with very high resolutions. Many commercial satellites have achieved spatial resolutions in the range of sub-meter and the revisit cycle has also shortened to one day. Currently, the most commonly used high resolution commercial satellites include QuickBird, GeoEye-1 and Worldview, and the highest achievable resolution is 0.31 meter. It is expected that higher resolution will be available in the future, which makes it possible to inspect power transmission lines by using the satellite sensing technologies. To this end, it has to extract linear features from remote sensing images.
However, power transmission lines are very weak linear objects in remote sensing images and have the characteristics of having fine dimension (in the order of sub-meters) and complicated backgrounds. Due to such facts, various problems such as false alarms are caused when using conventional technologies to identify such weak objects, with very strong ambient noise and system noise surrounding the objects to be identified. Moreover, conventional linear object identification methods have difficulty in handling short line segments. Therefore, there needs a method and apparatus for identifying weak linear objects from high resolution remote sensing images and it is desirable that such a method and apparatus can identify short line segments as well.